RLWRLD is a leading Physical AI company developing a Robotics Foundation Model (RFM) that enables robots to perceive, reason, and act in the real world like humans.
Building on deep research capabilities in AI and robotics and a strong data collaboration network with industrial partners in Japan, Korea, and beyond, RLWRLD is rapidly advancing our RFM to enable precise manipulation by high-degree-of-freedom robotic hands. The company is also collaborating with world-class research groups and partners in robotics and sensor solutions to develop AI models that can be practically deployed across industries such as manufacturing, logistics, and services.
Having raised approximately KRW 60 billion in cumulative seed funding from leading domestic and global venture capital firms and major corporations, RLWRLD continues to attract exceptional talent who are eager to drive innovation across AI, robotics technology, and business.
About the Product Organization
At RLWRLD, our Product Organization is responsible for developing all core products — spanning planning, development, and research.
We are building foundational technologies such as:
- Robotics Foundation Model (RFM)
- APIs/SDKs to deliver RFM functionality
- Data pipeline & teleoperation tools
- Training systems for model learning
- Benchmark systems to test performance
- Robot control systems
- Infra stack (GPU orchestration, compute management)
Our team includes both research and software engineers, working fluidly across AI model development and software infrastructure. We collaborate closely with Academy Researchers, robotic hardware partners, and internal business developers to deliver cutting-edge robotics solutions.
Position Overview
We are seeking talented individuals who can develop and apply innovative AI-based robot control models. In this role, you will leverage AI modeling techniques to represent complex robotic system components—such as motion, appearance, and sensor interactions—to achieve optimal performance in real-world environments. You will also play a key role in designing and optimizing high-performance model architectures required for next-generation robotics systems, laying the foundation for robots to learn and operate more intelligently and efficiently.
Join us at the forefront of future robotics innovation, where your creativity and expertise can truly shine. We look forward to taking on new challenges and growing together with you.
Key Responsibilities
- Research & development of VLA and action-generation models
- Design model architectures that jointly process image, video, and language data along with robot actions
- Apply and optimize deep learning techniques for effective multimodal information processing
- Building models based on Imitation Learning
- Develop algorithms that learn robot control policies using demonstration data
- Design data collection and preprocessing pipelines, as well as model validation workflows
- Reinforcement Learning–based policy training
- Improve robot control performance using RL algorithms (policy-based, value-based, etc.)
- Research algorithms that ensure efficient and stable training in both simulation and real environments
- Validation of research outcomes & collaboration
- Test and analyze model performance comprehensively in simulation and real-robot environments
- Collaborate with robotics system engineers, software engineers, and related teams to integrate models and identify improvements
Required Qualifications
- Strong knowledge of machine learning and deep learning
- Understanding and hands-on experience with core model architectures such as Neural Networks, CNN/RNN, and Transformers
- Experience in vision or language model research/development
- Ability to design and implement vision or language models
- Programming skills
- Ability to develop and optimize robotics AI models using programming languages such as Python and C++
- Proficiency with version control systems such as Git
Preferred Qualifications
- Understanding of Imitation Learning and Reinforcement Learning
- Experience applying imitation learning algorithms (DAgger, Behavior Cloning, etc.) and RL algorithms (Q-learning, Policy Gradients, etc.)
- Experience training policies in both simulation and real-world environments
- Experience in robotics or autonomous driving projects
- Experience integrating models in real or simulated environments using ROS, MuJoCo, Isaac Sim, etc.
- Experience with distributed and parallel training environments
- Hands-on experience training and optimizing large-scale models on GPU clusters or HPC systems
- Experience with data pipelines and MLOps
- Experience in ML lifecycle automation such as data management, model serving, and CI/CD
- Mathematical and statistical analysis skills
- Understanding of probability theory, optimization theory, and mathematical foundations of reinforcement learning
- Research publication & conference presentation experience
- Experience publishing or presenting robotics-AI-related papers at top-tier conferences/journals (ICRA, IROS, NeurIPS, etc.)
Working Conditions
- Duration: 3–6 months (Full-time offer may follow based on performance)
- Working hours: Monday to Friday, 09:00 – 18:00 (Flexible start time negotiable)
- Location: RUBINA Building, 561 Seolleung-ro, Gangnam-gu, Seoul, Korea
How to Apply
- Application Materials
- Resume in English or Korean
- (optional) Portfolio, research materials, or project documents showcasing your capabilities
- Application Deadline: Rolling basis
Hiring Process
- Document Screening → Interview Round → Final Offer
- Candidates who pass the document screening will be contacted individually.
- Additional interview rounds may be conducted if necessary.
Work Environment & Support
- Flexible Work Schedule: Adjust your working hours autonomously to match your personal rhythm.
- Equipment & Software Support: We provide job-specific equipment and essential software required for your role.
- Office Amenities: Enjoy our in-office snack bar and coffee machines.
- Holiday & Birthday Gifts: Small gifts are provided for holidays and birthdays.
- Health Checkup Support: We support your well-being through regular health checkups.
RLWRLD is a leading Physical AI company developing a Robotics Foundation Model (RFM) that enables robots to perceive, reason, and act in the real world like humans.
Building on deep research capabilities in AI and robotics and a strong data collaboration network with industrial partners in Japan, Korea, and beyond, RLWRLD is rapidly advancing our RFM to enable precise manipulation by high-degree-of-freedom robotic hands. The company is also collaborating with world-class research groups and partners in robotics and sensor solutions to develop AI models that can be practically deployed across industries such as manufacturing, logistics, and services.
Having raised approximately KRW 60 billion in cumulative seed funding from leading domestic and global venture capital firms and major corporations, RLWRLD continues to attract exceptional talent who are eager to drive innovation across AI, robotics technology, and business.
About the Product Organization
At RLWRLD, our Product Organization is responsible for developing all core products — spanning planning, development, and research.
We are building foundational technologies such as:
- Robotics Foundation Model (RFM)
- APIs/SDKs to deliver RFM functionality
- Data pipeline & teleoperation tools
- Training systems for model learning
- Benchmark systems to test performance
- Robot control systems
- Infra stack (GPU orchestration, compute management)
Our team includes both research and software engineers, working fluidly across AI model development and software infrastructure. We collaborate closely with Academy Researchers, robotic hardware partners, and internal business developers to deliver cutting-edge robotics solutions.
Position Overview
We are seeking talented individuals who can develop and apply innovative AI-based robot control models. In this role, you will leverage AI modeling techniques to represent complex robotic system components—such as motion, appearance, and sensor interactions—to achieve optimal performance in real-world environments. You will also play a key role in designing and optimizing high-performance model architectures required for next-generation robotics systems, laying the foundation for robots to learn and operate more intelligently and efficiently.
Join us at the forefront of future robotics innovation, where your creativity and expertise can truly shine. We look forward to taking on new challenges and growing together with you.
Key Responsibilities
- Research & development of VLA and action-generation models
- Design model architectures that jointly process image, video, and language data along with robot actions
- Apply and optimize deep learning techniques for effective multimodal information processing
- Building models based on Imitation Learning
- Develop algorithms that learn robot control policies using demonstration data
- Design data collection and preprocessing pipelines, as well as model validation workflows
- Reinforcement Learning–based policy training
- Improve robot control performance using RL algorithms (policy-based, value-based, etc.)
- Research algorithms that ensure efficient and stable training in both simulation and real environments
- Validation of research outcomes & collaboration
- Test and analyze model performance comprehensively in simulation and real-robot environments
- Collaborate with robotics system engineers, software engineers, and related teams to integrate models and identify improvements
Required Qualifications
- Strong knowledge of machine learning and deep learning
- Understanding and hands-on experience with core model architectures such as Neural Networks, CNN/RNN, and Transformers
- Experience in vision or language model research/development
- Ability to design and implement vision or language models
- Programming skills
- Ability to develop and optimize robotics AI models using programming languages such as Python and C++
- Proficiency with version control systems such as Git
Preferred Qualifications
- Understanding of Imitation Learning and Reinforcement Learning
- Experience applying imitation learning algorithms (DAgger, Behavior Cloning, etc.) and RL algorithms (Q-learning, Policy Gradients, etc.)
- Experience training policies in both simulation and real-world environments
- Experience in robotics or autonomous driving projects
- Experience integrating models in real or simulated environments using ROS, MuJoCo, Isaac Sim, etc.
- Experience with distributed and parallel training environments
- Hands-on experience training and optimizing large-scale models on GPU clusters or HPC systems
- Experience with data pipelines and MLOps
- Experience in ML lifecycle automation such as data management, model serving, and CI/CD
- Mathematical and statistical analysis skills
- Understanding of probability theory, optimization theory, and mathematical foundations of reinforcement learning
- Research publication & conference presentation experience
- Experience publishing or presenting robotics-AI-related papers at top-tier conferences/journals (ICRA, IROS, NeurIPS, etc.)
Working Conditions
- Duration: 3–6 months (Full-time offer may follow based on performance)
- Working hours: Monday to Friday, 09:00 – 18:00 (Flexible start time negotiable)
- Location: RUBINA Building, 561 Seolleung-ro, Gangnam-gu, Seoul, Korea
How to Apply
- Application Materials
- Resume in English or Korean
- (optional) Portfolio, research materials, or project documents showcasing your capabilities
- Application Deadline: Rolling basis
Hiring Process
- Document Screening → Interview Round → Final Offer
- Candidates who pass the document screening will be contacted individually.
- Additional interview rounds may be conducted if necessary.
Work Environment & Support
- Flexible Work Schedule: Adjust your working hours autonomously to match your personal rhythm.
- Equipment & Software Support: We provide job-specific equipment and essential software required for your role.
- Office Amenities: Enjoy our in-office snack bar and coffee machines.
- Holiday & Birthday Gifts: Small gifts are provided for holidays and birthdays.
- Health Checkup Support: We support your well-being through regular health checkups.